| ObjectiveThis study aims to analyze the epidemiological characteristics of dengue fever and hand,foot,and mouth disease that have occurred in China in recent years and to understand their epidemic patterns.Using different timescales(year,month,and week),the correlations between dengue fever、hand-foot-mouth and meteorological factors,the key meteorological factors affecting disease incidence,and the synergistic effects of different meteorological factors on disease incidence were analyzed.Risk factors affecting the incidence of infectious diseases were investigated from the meteorological perspective.Based on the analyses on correlation and synergism,a quantitative mathematical model was constructed to predict the trend of infectious disease incidence and provide supporting data for the prevention and control of infectious diseases.MethodsData collected for the study included the following: number of dengue fever cases reported in Guangdong from 2008-2016;number of HFMD cases in China reported from 2006-2016;meteorological data during the same period(highest barometric pressure,lowest barometric pressure,average barometric pressure,highest temperature,lowest temperature,average temperature,average relative humidity,fastest wind speed,maximum wind speed);and demographic data during the same period.Descriptive epidemiological methods were used to analyze the distribution characteristics and dynamic trends of dengue fever and HFMD.Arc GIS was used to describe the differences in geographical distributions of dengue fever and HFMD from the provincial and prefecture levels,respectively.Spearman rank correlation was used to analyze the correlations between meteorological factors and the diseases.Smoothed line graphs,the Ross-Macdonald model,and the Watts model were used to calculate the threshold temperature,which was a key meteorological factor.The synergistic effects among meteorological factors were analyzed by SPSS data conversion and multivariate analysis of variance.The model was constructed using linear models,exponential models,logarithmic models,power functions,and inverse normal cumulative distribution functions multiple regression.Results1.Between 2008 and 2016,there were 51,130 cases of dengue fever in the Guangdong province,with differences in the annual incidence.The incidence of dengue fever was the highest in 2014,with a total of 45,190 cases,accounting for 88.50% of all cases.When the data were analyzed using week as the unit,the cases were found to be concentrated between the 38 th week to the 42 nd week of the year,i.e.,September and October.Six deaths occurred(all in 2014)and the mortality rate was 1.17/?.2.Dengue fever was reported in all age groups,but mostly in young adults.The age group with the highest incidence rates was 20-59 years,accounting for 70.91% of all cases.Patients aged 0-9 years,10-19 years,and over 60 years accounted for 4.19%,7.32%,and 17.58%,respectively,of all cases.Between 2008 and 2016,there were 25,351 cases,which occurred in males and 25,779,which occurred in females.The male-to-female ratio was 0.98:1.Professional groups with the highest incidence of the diseases included housekeepers,the unemployed,retirees,business service and workers,as well as students.These five groups of professionals accounted for 64.11% of the total number of cases.3.Regarding geographical distribution,the pattern of dengue fever incidence varied among cities within the Guangdong province.Regions with the highest incidence were mainly concentrated in the Pearl River Delta region of the Guangdong province(nine regions including Guangzhou,Shenzhen,Foshan,Dongguan,Zhongshan,Zhuhai,Jiangmen,Zhaoqing,and Huizhou),which accounted for 93.86% of all cases.4.The weekly meteorological factors and weekly number of cases of dengue fever was analyzed by the Spearman rank correlation.The analyses showed that the highest temperature(r=0.373 P<0.01),lowest temperature(r=0.337 P<0.01),and average temperature(r=0.386 P<0.01),were positively correlated with dengue fever incidence,whereas the highest barometric pressure(r=-0.244 P<0.01),lowest barometric pressure(r=-0.219 P<0.01),and average barometric pressure(r=-0.239 P<0.01),were negatively correlated with dengue fever incidence.5.Smoothed line graphs and the Ross-Macdonald and Watts models showed that the threshold for the lowest temperature in relation to the increased number of cases of dengue fever was 18°C.That is,when the lowest temperature was greater than 18°C,the incidence of dengue fever was significantly higher.6.At 18°C as the cutting point,when the thelowest temperature is less than18°C,factors affecting the incidence of dengue fever were average temperature(r=0.276 P<0.05)、maximum temperature(r=0.218 P<0.05)、the lowest temperature(r=0.230 P<0.05);when the lowest temperature greater than18°C,factors affecting the incidence of dengue fever were average temperature(r=0.153 P<0.05)、maximum pressure(r=0.127 P<0.05)、the lowest pressure(r=0.125 P<0.05)、mean pressure(r=0.124 P<0.05)、he average relative humidity(r=-0.221 P<0.01).7.Multivariate analysis of variance indicated interactions among the lowest barometric pressure,average relative humidity,average temperature,and dengue fever epidemic.When only the effect of temperature was considered,the dengue incidence changed exponentially with the average temperature,with y = 3.2803e1.8301xR2 = 0.8645.For every 1°C increase in temperature,the theoretical number of cases increased by 523.45%.If the interactions between the lowest barometric pressure and average temperature were taken into account,the exponential equation changed to y = 2.8368e0.7301xR2 = 0.59,with a decreasing incidence trend.For every 1°C increase in temperature,the theoretical number of cases increased by 107.53%.Based on these results and further considering the interactions among the average relative humidity,the lowest barometric pressure,and the average temperature,the incidence rate changed linearly,with y = 1406.4x-1554.3 R2= 0.5766.The incidence trend was further decreased.For every 1°C increase in temperature,the number of cases increased by 5.9%.Further analyses were performed by combining different interactive meteorological factors to different groups.The results showed that dengue fever has the highest epidemic intensity at an average temperature of 25-28°C,a lowest pressure of 997-1002 h Pa,and an average relative humidity of 73%-81%.The number of weekly incidence was also the highest under these conditions(17,571 cases).8.The improved Logit model,i.e.,the inverse normal cumulative distribution function model,accounted for variables including key meteorological factors(average temperature,highest barometric pressure,lowest barometric pressure,average barometric pressure,and average relative humidity)and interactive meteorological factors(average temperature*lowest barometric pressure,average temperature*lowest barometric pressure*average relative humidity),insect vector factor,and import factor.The model had a high fitness index R2 value,with the goodness of fit of 0.9248.The prediction of the number of dengue fever cases in weeks 1-41 of 2017 had confirmed the reliability of our model.9.In China,the annual number of cases and incidence rates of HFMD showed an upward trend from 2006 to 2014(13,637 cases [1.05 per 100 thousand] in 2006;2,781,719 cases [204.17 per 100 thousand] in 2014).Although the number of cases and incidence rates of the disease decreased in 2015(1,997,500 cases [104.25/100 thousand] in 2015),but the incidence rates increased in 2016(2,442,111cases[145.71/100 thousand]),which indicates the prevention and control of the disease remained a challenge.10.The mortality rates of HFMD initially increased,followed by a decrease.The mortality rate was 0.2‰ in 2007 and reached the highest value of 0.51‰ in 2010.The mortality rate has since continued to decrease from 2010(0.51‰ in 2010 and 0.066‰ in 2015),dropping nearly 85.66%.11.HFMD displayed distinct distribution characteristics among the populations.The number of male patients was 1.59 times that of females.Most patients were children under the age of 10(accounting for 98.56%),of which patients aged 0-1 years accounted for 9.2% 、patients aged 1-4 years accounted for 80.41% and those aged 5-9 years accounted for 8.96%.Furthermore,based on the data collected in the past 11 years,the proportion of the 0 and 1 year old age groups is on the rise as a whole(the 0 year old age group increased from 6.43% to 8.64%,and the 1 year old group increased from 12.41% to 30.55%);the proportion of the 4 and 5 year old age groups is on the decrease as a whole(the 4 year old age group decreased from 17.39% to 10.56%,and the 5 year old group decreased from 9.51% to 4.83%);the proportion of the 2 and 3 year old age groups remained unchanged.12.Significant spatial differences in HFMD were observed.In 2006-2009 years,the number of cases in Shandong,Henan and Hebei accounted for the most,accounting for 27.23% of the total number of cases in 2006-2009 years.After 2010,the number of cases in Guangdong and Guangxi increased gradually.In 9 years,the number of the two provinces in the south of China accounted for 25.38% of the total incidence(15.32% in Guangdong province and 10.06% in Guangxi).The incidence rate was calculated based on the 2006-2016 census data,the average annual incidence rate of three provinces in the area in the South(Guangdong: 25.18?,Guangxi: 36.09?,Hainan: 41.62?).13.The meteorological data of 31 provinces in China were analyzed.These included highest barometric pressure,lowest barometric pressure,average barometric pressure,highest temperature,lowest temperature,average temperature,average relative humidity,fastest wind speed,maximum wind speed.The results showed that the lowest temperature、average temperature、 highest temperature andmaximum wind speed were closely related to the incidence rates of HFMD and showed a good fit in the exponential model.The relationship between average temperature(x)and incidence rate(y)was y = 2.7407e0.1033 x,with a coefficient of determination R2 of 0.74.The relationship between lowest temperature(x)and incidence rate(y)was y = 4.7539e0.0849 x,with a coefficient of determination R2 of 0.74.The relationship between highest temperature(x)and incidence rate(y)was y = 1.1285e0.1164 x,with a coefficient of determination R2 of 0.69.The relationship between maximum wind speed(x)and incidence rate(y)was y = 0.5813e0.6782 x,with a coefficient of determination R2 of 0.52.Conclusions1.The incidence of dengue fever in Guangdong province has obvious time and spatial aggregation.The onset time is mainly concentrated in between the 38 th and 42 nd week of each year,and the location of the disease is mainly in the economically developed Pearl River Delta region.The use of different timescales(year,month,and week)had an effect on the correlation between the dengue fever incidence and meteorological factors.Data analyses using a more detailed scale(week)could more accurately reflect the correlation.2.The incidence of dengue fever in Guangdong province was associated with a clear threshold temperature.An average weekly lowest temperature of 18°C could be used as a warning for early dengue fever epidemic in the Guangdong province.Above this threshold,the incidence of dengue fever increased sharply.3.The meteorological factorsaffect the onset of dengue fever synergisticly.The key meteorological factors affecting the onset of dengue fever are temperature,pressure and humidity when the minimum temperature is greater than 18°C.When the minimum temperature is less than 18 °C,the key meteorological factors that affect dengue fever are only temperature.Moreover,the minimum air pressure and average relative humidity affect dengue fever synergisticly when the minimum temperature is greater than 18.Dengue fever has the highest epidemic intensity at an average temperature of 25-28 °C,a lowest pressure of 997-1002 h Pa,and an average relative humidity of 73%-81%.4.In addition to meteorological factors,the construction of the dengue fever prediction model should also consider factors such as insect vectors and special events(e.g.,extreme weather,imported cases).The inverse normal cumulative distribution model constructed based on these factors could effectively predict and secure warnings on dengue fever epidemic in the Guangdong province.5.The incidence rate of HFMD has continued to rise in the past 11 years and reached the peak in 2014.The death rate of hand foot and mouth disease increased first and then declined,and the mortality rate was the highest in 2010,and then decreased year by year.The proportion of children under 0 years old and 1 years old age group is increasing,which should be given proper hygiene,health education,and medical treatment.6.The incidence rates of HFMD showed significant spatial differences.Before 2010,Shandong,Henan and Hebei had high incidence of hand foot and mouth disease.After2010,Guangdong,Guangxi and Hainan were developing frequently,whichshowed a trend towards higher temperature in southern China.7.HFMD incidence was mainly associated with the annual average temperature 、lowest temperature、highest temperature and maximum speed.The temperature is the main factor affecting the hand foot and mouth disease,with Exponential model,which means the small temperature change can lead to the increase of hand foot and mouth disease.Significance and Novelty1.This study used a large volume of data spanning across a wide timeframe,which could better reflect the patterns of disease incidence from precise timescales.This approach allowed the study to provide a reliable theoretical basis for disease prevention and control.2.The analyses of dengue fever epidemics in the Guangdong province using different timescales provided a good perspective for investigating the epidemic patterns of the disease.We identified the key meteorological factors affecting the disease,and determined that dengue fever epidemic was associated with a clear-cut threshold temperature.Above such threshold temperature,lowest pressure and average relative humidity synergistically affected the epidemic of dengue fever.3.Our model,constructed based on synergistic factors,insect vectors,and import factors,was the first of its kind to predict dengue fever on a weekly timescale,which improved the accuracy and timeliness of dengue fever prediction.4.From the epidemic of HFMD and correlation with meteorological analysis,we found people should focus on the prevention and control of hand foot mouth disease on 0 years old and 1 years old age group 、HFMD changed from the inland plain area to South area with high temperature and temperature affect the incidence of HFMD in exponential model. |
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